customizedTraining
Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models
Customized training is a simple technique for transductive learning, when the test covariates are known at the time of training. The method identifies a subset of the training set to serve as the training set for each of a few identified subsets in the training set. This package implements customized training for the glmnet() and cv.glmnet() functions.
- Version1.2
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release01/29/2019
Documentation
Team
Scott Powers
Trevor Hastie
Robert Tibshirani
Insights
Last 30 days
This package has been downloaded 226 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 12 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,323 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jan 10, 2025 with 28 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages